At a Glance
- Tasks: Build and optimise backend systems for AI-powered applications that enhance user experience.
- Company: Join a cutting-edge tech company focused on creating proactive, intelligent applications.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborative, fast-paced environment with a focus on innovation and learning.
- Why this job: Be at the forefront of AI technology and make a real difference in users' lives.
- Qualifications: Experience with high-throughput services and familiarity with AI inference patterns.
The predicted salary is between 63000 - 77000 £ per year.
There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native.
Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting.
We aim to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.
Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion.
We believe products will greatly reduce hallucinations
Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things
Role
As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product.
Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience.
Build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients.
- Focus
- Build and operate backend systems that serve AI-powered features in production.
- Design inference pipelines and orchestration layers that handle multi-step workflows, tool calls, and retries
- Manage the full lifecycle of AI requests: routing, caching, batching, streaming, and state management
- Optimize latency, throughput, and cost across model inference and downstream systems
- Design systems that remain reliable despite non-deterministic model behavior and external dependencies
- Implement observability for AI systems, including logging, tracing, and debugging of model outputs and failures
- Collaborate with ML and product teams to translate model capabilities into stable, production-grade APIs
- Ideal Experiences
- Experience running high-throughput, low-latency services.
- Familiarity with AI inference patterns (LLMs, embeddings, multimodal).
- Bias toward shipping and learning from production behavior.
- Outcomes
- Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.
- Multi-step AI workflows complete successfully across tools and services, with robust handling of failures and retries
- APIs are stable, clear, and support seamless integration with frontend and ML systems.
- Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact.
- Iterative improvements based on real usage continuously increase system performance and reliability.
- System design evolves to support increasing scale, complexity, and new AI capabilities without major rewrites.
- Python
- Node Js
- Pytorch
- Open AI / Anthropic / open-source LLMs
- SQl & no SQL
- Docker
- How We Work
The best products today in the world were built by small, world class teams.
We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning.
Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product
#J-18808-Ljbffr
Backend Engineer, AI Systems employer: ActAI
At ActAI, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a High-Impact Operations Manager, you will benefit from unparalleled growth opportunities, working alongside innovative leaders in a fast-paced environment that values collaboration and creativity. Our commitment to employee development and well-being makes ActAI an exceptional place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land Backend Engineer, AI Systems
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at ActAI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ActAI.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like ActAI.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like ActAI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Backend Engineer, AI Systems
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ActAI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ActAI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at ActAI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ActAI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
